Introduction to Stochastic Search and Optimization | 
 enlarge | Author: James C. Spall
Publisher: Wiley-Interscience
Category: Book
List Price: $134.50
Buy New: $102.22
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Rating:  2 reviews
Sales Rank: 744728
Media: Hardcover
Edition: 1st
Pages: 618
Number Of Items: 1
Shipping Weight (lbs): 2.8
Dimensions (in): 10 x 7.1 x 1.5
ISBN: 0471330523
Dewey Decimal Number: 519.2
EAN: 9780471330523
Publication Date: March 2003
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| Editorial Reviews:
Product Description
- Unique in its survey of the range of topics.
- Contains a strong, interdisciplinary format that will appeal to both students and researchers.
- Features exercises and web links to software and data sets.
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| Customer Reviews:
Recommended to scholars and graduate students September 23, 2003
19 out of 21 found this review helpful
Introduction to Stochastic Search and Optimization provides comprehensive, current information on methods for real-world problem solving, including stochastic gradient and non-gradient techniques, as well as relatively recent innovations such as simulated annealing, genetic algorithms, and MCMC. It is written to be read and understood by graduate students, industrial practitioners, and experienced researchers in the field. Web links to software and data sets, and an extensive list of references of the book allows the reader to explore deeper into certain topic areas. I also found the index to be very comprehensive and carefully done. The appendices are as a refresher and summary of much of the prerequisite material. The book is somewhat unique in providing a balanced discussion of algorithms, including both their strengths and weaknesses. The book is among very few books that have integrated essential parts of statistical fields with optimization and decision making. The book's inclusion of a chapter on optimal experimental design is an example of such integration. The approaches discussed in the book could be used for financial decision making, forecasting, and quality improvement, among many other areas.
Great book!!! December 7, 2004
Wagner F. Sacco (Atlanta, GA)
4 out of 9 found this review helpful
A must have for anyone interested in otimization! Extremely well written and objective.
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